Something I am not clear about is the algorithm used. Or is it just a test on a single<br>processor version by giving it more time to search? If the tree is not shared as in the 'root parallelization' <br>scheme, I have doubts if it can search 'deeper' even though nps scales almost perfectly.<br>
By deeper ,I mean more expansion to the best moves. Since the processors are not searching the same tree , <br>it seems to me the search in parallel is wider (more alternatives) but not necessarily deeper searched.<br>Or is this taken care of by using a lower exploration constant (c) for the parallel search in the hope that<br>
it would fill the void introduced by adding more selectivity ?<br> <br><br><div class="gmail_quote">On Mon, Mar 28, 2011 at 5:49 AM, Gian-Carlo Pascutto <span dir="ltr"><<a href="mailto:gcp@sjeng.org">gcp@sjeng.org</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;"><div class="im">>However one of my early observations with Go programming has been<br>
>that the speed is not a very big issue in this field (at least in lower<br>
levels).<br>
</div>>[...]<br>
<div class="im">>10x more processing power only gave around 100 extra elo points.<br>
><br>
><br>
>Of course with heavy playouts and more fine tuned programs things can<br>
>be very different...<br>
<br>
</div>No. You probably have some other problem or bugs. See for example this<br>
study:<br>
<br>
<a href="http://cgos.boardspace.net/study/13/index.html" target="_blank">http://cgos.boardspace.net/study/13/index.html</a><br>
<br>
Leela Lite was using light playouts. The slope is a bit flatter than the<br>
real program, but not much more so. You should get far more than 100 ELO for<br>
a 10x speedup.<br>
<br>
--<br>
<font color="#888888">GCP<br>
</font><div><div></div><div class="h5"><br>
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